make linspace arg a float

src/arg_desc.jl

@@ -21,7 +21,7 @@ const _arg_desc = KW(
 :markerstrokewidth 	=> "Number. Width of the marker stroke (border. in pixels)",
 :markerstrokecolor 	=> "Color Type. Color of the marker stroke (border).  `:match` will take the value from `:foreground_color_subplot`.",
 :markerstrokealpha 	=> "Number in [0,1]. The alpha/opacity override for the marker stroke (border).  `nothing` (the default) means it will take the alpha value of markerstrokecolor.",
-:bins              	=> "Integer, NTuple{2,Integer}, AbstractVector or Symbol. Default is :auto (the Freedman-Diaconis rule). For histogram-types, defines the approximate number of bins to aim for, or the auto-binning algorithm to use (:sturges, :sqrt, :rice, :scott or :fd). For fine-grained control pass a Vector of break values, e.g. `linspace(extrema(x)..., 25)`",
+:bins              	=> "Integer, NTuple{2,Integer}, AbstractVector or Symbol. Default is :auto. For histogram-types, defines the approximate number of bins to aim for, or the auto-binning algorithm to use (:sturges, :sqrt, :rice, :scott or :fd). For fine-grained control pass a Vector of break values, e.g. `linspace(extrema(x)..., 25)`",
 :smooth            	=> "Bool.  Add a regression line?",
 :group             	=> "AbstractVector. Data is split into a separate series, one for each unique value in `group`.",
 :x                 	=> "Various. Input data. First Dimension",
@@ -40,7 +40,7 @@ const _arg_desc = KW(
 :ribbon            	=> "Number or AbstractVector.  Creates a fillrange around the data points.",
 :quiver            	=> "AbstractVector or 2-Tuple of vectors.  The directional vectors U,V which specify velocity/gradient vectors for a quiver plot.",
 :arrow             	=> "nothing (no arrows), Bool (if true, default arrows), Arrow object, or arg(s) that could be style or head length/widths.  Defines arrowheads that should be displayed at the end of path line segments (just before a NaN and the last non-NaN point).  Used in quiverplot, streamplot, or similar.",
-:normalize         	=> "Bool or Symbol. Histogram normalization mode. Possible values are: false/:none (no normalization, default), true/:pdf (normalize to a discrete Probability Density Function, where the total area of the bins is 1), :probability (bin heights sum to 1) and :density (the area of each bin, rather than the height, is equal to the counts - useful for uneven bin sizes).",
+:normalize         	=> "Bool or Symbol. Histogram normalization mode. Possible values are: false/:none (no normalization, default), true/:pdf (normalize to a PDF with integral of 1) and :density (only normalize in respect to bin sizes).",
 :weights           	=> "AbstractVector. Used in histogram types for weighted counts.",
 :contours          	=> "Bool. Add contours to the side-grids of 3D plots?  Used in surface/wireframe.",
 :match_dimensions  	=> "Bool. For heatmap types... should the first dimension of a matrix (rows) correspond to the first dimension of the plot (x-axis)?  The default is false, which matches the behavior of Matplotlib, Plotly, and others.  Note: when passing a function for z, the function should still map `(x,y) -> z`.",

src/args.jl

@@ -80,13 +80,9 @@ const _typeAliases = Dict{Symbol,Symbol}(
 
 add_non_underscore_aliases!(_typeAliases)
 
-const _histogram_like = [:histogram, :barhist, :barbins]
-const _line_like = [:line, :path, :steppre, :steppost]
-const _surface_like = [:contour, :contourf, :contour3d, :heatmap, :surface, :wireframe, :image]
-
-like_histogram(seriestype::Symbol) = seriestype in _histogram_like
-like_line(seriestype::Symbol)      = seriestype in _line_like
-like_surface(seriestype::Symbol)   = seriestype in _surface_like
+like_histogram(seriestype::Symbol) = seriestype in (:histogram, :barhist, :barbins)
+like_line(seriestype::Symbol)      = seriestype in (:line, :path, :steppre, :steppost)
+like_surface(seriestype::Symbol)   = seriestype in (:contour, :contourf, :contour3d, :heatmap, :surface, :wireframe, :image)
 
 is3d(seriestype::Symbol) = seriestype in _3dTypes
 is3d(series::Series) = is3d(series.d)
@@ -866,7 +862,7 @@ function extractGroupArgs(v::AVec, args...; legendEntry = string)
     if n > 100
         warn("You created n=$n groups... Is that intended?")
     end
-    groupIds = Vector{Int}[filter(i -> v[i] == glab, linearindices(v)) for glab in groupLabels]
+    groupIds = Vector{Int}[filter(i -> v[i] == glab, 1:length(v)) for glab in groupLabels]
     GroupBy(map(legendEntry, groupLabels), groupIds)
 end
 
@@ -874,7 +870,7 @@ legendEntryFromTuple(ns::Tuple) = string(("$n " for n in ns)...)
 
 # this is when given a tuple of vectors of values to group by
 function extractGroupArgs(vs::Tuple, args...)
-    (vs == ()) && return GroupBy([""], [indices(args[1],1)])
+    (vs == ()) && return GroupBy([""], [1:size(args[1],1)])
     v = collect(zip(vs...))
     extractGroupArgs(v, args...; legendEntry = legendEntryFromTuple)
 end
@@ -983,8 +979,7 @@ convertLegendValue(v::AbstractArray) = map(convertLegendValue, v)
 # anything else is returned as-is
 function slice_arg(v::AMat, idx::Int)
     c = mod1(idx, size(v,2))
-    m,n = indices(v)
-    size(v,1) == 1 ? v[first(m),n[c]] : v[:,n[c]]
+    size(v,1) == 1 ? v[1,c] : v[:,c]
 end
 slice_arg(wrapper::InputWrapper, idx) = wrapper.obj
 slice_arg(v, idx) = v

src/axes.jl

@@ -461,10 +461,10 @@ end
 
 # add the discrete value for each item.  return the continuous values and the indices
 function discrete_value!(axis::Axis, v::AVec)
-    n = linearindices(v)
-    cvec = zeros(length(n))
-    discrete_indices = zeros(Int, length(n))
-    for i=n
+    n = length(v)
+    cvec = zeros(n)
+    discrete_indices = zeros(Int, n)
+    for i=1:n
         cvec[i], discrete_indices[i] = discrete_value!(axis, v[i])
     end
     cvec, discrete_indices
@@ -472,10 +472,10 @@ end
 
 # add the discrete value for each item.  return the continuous values and the indices
 function discrete_value!(axis::Axis, v::AMat)
-    n,m = indices(v)
-    cmat = zeros(v)
-    discrete_indices = similar(Array{Int}, n, m)
-    @inbounds for i=n, j=m
+    n,m = size(v)
+    cmat = zeros(n,m)
+    discrete_indices = zeros(Int, n, m)
+    for i=1:n, j=1:m
         cmat[i,j], discrete_indices[i,j] = discrete_value!(axis, v[i,j])
     end
     cmat, discrete_indices

src/backends/glvisualize.jl

@@ -784,7 +784,7 @@ end
 
 function gl_bar(d, kw_args)
     x, y = d[:x], d[:y]
-    nx, ny = length(linearindices(x)), length(linearindices(y))
+    nx, ny = length(x), length(y)
     axis = d[:subplot][isvertical(d) ? :xaxis : :yaxis]
     cv = [discrete_value!(axis, xi)[1] for xi=x]
     x = if nx == ny
@@ -792,7 +792,7 @@ function gl_bar(d, kw_args)
     elseif nx == ny + 1
         0.5diff(cv) + cv[1:end-1]
     else
-        error("bar recipe: x must be same length as y (centers), or one more than y (edges).\n\t\tlength(x)=$(nx), length(y)=$(ny)")
+        error("bar recipe: x must be same length as y (centers), or one more than y (edges).\n\t\tlength(x)=$(length(x)), length(y)=$(length(y))")
     end
     if haskey(kw_args, :stroke_width) # stroke is inside for bars
         #kw_args[:stroke_width] = -kw_args[:stroke_width]
@@ -802,7 +802,7 @@ function gl_bar(d, kw_args)
     hw = if bw == nothing
         ignorenan_mean(diff(x))
     else
-        Float64[_cycle(bw,i)*0.5 for i=linearindices(x)]
+        Float64[_cycle(bw,i)*0.5 for i=1:length(x)]
     end
 
     # make fillto a vector... default fills to 0
@@ -852,11 +852,11 @@ function gl_boxplot(d, kw_args)
     sx, sy = m[1,1], m[2,2]
     for (i,glabel) in enumerate(glabels)
         # filter y
-        values = y[filter(i -> _cycle(x,i) == glabel, linearindices(y))]
+        values = y[filter(i -> _cycle(x,i) == glabel, 1:length(y))]
         # compute quantiles
         q1,q2,q3,q4,q5 = quantile(values, linspace(0,1,5))
         # notch
-        n = Plots.notch_width(q2, q4, length(linearindices(values)))
+        n = Plots.notch_width(q2, q4, length(values))
         # warn on inverted notches?
         if notch && !warning && ( (q2>(q3-n)) || (q4<(q3+n)) )
             warn("Boxplot's notch went outside hinges. Set notch to false.")
@@ -963,7 +963,7 @@ function scale_for_annotations!(series::Series, scaletype::Symbol = :pixels)
         # with a list of custom shapes for each
         msw, msh = anns.scalefactor
         offsets = Array{Vec2f0}(length(anns.strs))
-        series[:markersize] = map(linearindices(anns.strs)) do i
+        series[:markersize] = map(1:length(anns.strs)) do i
             str = _cycle(anns.strs, i)
             # get the width and height of the string (in mm)
             sw, sh = text_size(str, anns.font.pointsize)
@@ -1077,7 +1077,7 @@ function _display(plt::Plot{GLVisualizeBackend}, visible = true)
                     kw = copy(kw_args)
                     fr = d[:fillrange]
                     ps = if all(x-> x >= 0, diff(d[:x])) # if is monotonic
-                        vcat(points, Point2f0[(points[i][1], _cycle(fr, i)) for i=reverse(linearindices(points))])
+                        vcat(points, Point2f0[(points[i][1], _cycle(fr, i)) for i=length(points):-1:1])
                     else
                         points
                     end
@@ -1291,8 +1291,8 @@ function gl_surface(x,y,z, kw_args)
         if isa(x, AbstractMatrix) && isa(y, AbstractMatrix)
             main = map(s->map(Float32, s), (x, y, z))
         elseif isa(x, AbstractVector) || isa(y, AbstractVector)
-            x = Float32[x[i] for i = indices(z,1), j = indices(z,2)]
-            y = Float32[y[j] for i = indices(z,1), j = indices(z,2)]
+            x = Float32[x[i] for i = 1:size(z,1), j = 1:size(z,2)]
+            y = Float32[y[j] for i = 1:size(z,1), j = 1:size(z,2)]
             main = (x, y, map(Float32, z))
         else
             error("surface: combination of types not supported: $(typeof(x)) $(typeof(y)) $(typeof(z))")
@@ -1301,7 +1301,7 @@ function gl_surface(x,y,z, kw_args)
             points = map(Point3f0, zip(vec(x), vec(y), vec(z)))
             faces = Cuint[]
             idx = (i,j) -> sub2ind(size(z), i, j) - 1
-            for i=indices(z,1), j=indices(z,2)
+            for i=1:size(z,1), j=1:size(z,2)
 
                 i < size(z,1) && push!(faces, idx(i, j), idx(i+1, j))
                 j < size(z,2) && push!(faces, idx(i, j), idx(i, j+1))

src/backends/gr.jl

@@ -306,7 +306,7 @@ end
 function gr_draw_markers(series::Series, x, y, msize, mz)
     shapes = series[:markershape]
     if shapes != :none
-        for i=linearindices(x)
+        for i=1:length(x)
             msi = _cycle(msize, i)
             shape = _cycle(shapes, i)
             cfunc = isa(shape, Shape) ? gr_set_fillcolor : gr_set_markercolor

src/backends/plotly.jl

@@ -370,7 +370,7 @@ end
 
 
 function plotly_colorscale(grad::ColorGradient, α)
-    [[grad.values[i], rgb_string(grad.colors[i])] for i in linearindices(grad.colors)]
+    [[grad.values[i], rgb_string(grad.colors[i])] for i in 1:length(grad.colors)]
 end
 plotly_colorscale(c, α) = plotly_colorscale(cgrad(alpha=α), α)
 # plotly_colorscale(c, alpha = nothing) = plotly_colorscale(cgrad(), alpha)
@@ -397,7 +397,7 @@ end
 # we split by NaNs and then construct/destruct the shapes to get the closed coords
 function plotly_close_shapes(x, y)
     xs, ys = nansplit(x), nansplit(y)
-    for i=linearindices(xs)
+    for i=1:length(xs)
         shape = Shape(xs[i], ys[i])
         xs[i], ys[i] = coords(shape)
     end

src/backends/pyplot.jl

@@ -244,7 +244,7 @@ end
 # end
 
 function get_locator_and_formatter(vals::AVec)
-    pyticker["FixedLocator"](linearindices(vals)), pyticker["FixedFormatter"](vals)
+    pyticker["FixedLocator"](1:length(vals)), pyticker["FixedFormatter"](vals)
 end
 
 function add_pyfixedformatter(cbar, vals::AVec)
@@ -589,7 +589,7 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
             shapes = series[:markershape]
             msc = py_markerstrokecolor(series)
             lw = py_dpi_scale(plt, series[:markerstrokewidth])
-            for i=linearindices(y)
+            for i=1:length(y)
                 extrakw[:c] = if series[:marker_z] == nothing
                     py_color_fix(py_color(_cycle(series[:markercolor],i)), x)
                 else
@@ -850,7 +850,7 @@ function py_add_series(plt::Plot{PyPlotBackend}, series::Series)
         kw = KW()
         if discrete_colorbar_values != nothing
             locator, formatter = get_locator_and_formatter(discrete_colorbar_values)
-            # kw[:values] = linearindices(discrete_colorbar_values)
+            # kw[:values] = 1:length(discrete_colorbar_values)
             kw[:values] = sp[:zaxis][:continuous_values]
             kw[:ticks] = locator
             kw[:format] = formatter

src/components.jl

@@ -89,7 +89,7 @@ end
 "create a shape by picking points around the unit circle.  `n` is the number of point/sides, `offset` is the starting angle"
 function makeshape(n; offset = -0.5, radius = 1.0)
     z = offset * π
-    Shape(partialcircle(z, z + 2π, n+1, radius))
+    Shape(partialcircle(z, z + 2π, n+1., radius))
 end
 
 
@@ -186,7 +186,7 @@ end
 function scale!(shape::Shape, x::Real, y::Real = x, c = center(shape))
     sx, sy = coords(shape)
     cx, cy = c
-    for i=linearindices(sx)
+    for i=1:length(sx)
         sx[i] = (sx[i] - cx) * x + cx
         sy[i] = (sy[i] - cy) * y + cy
     end
@@ -201,7 +201,7 @@ end
 "translate a Shape in space"
 function translate!(shape::Shape, x::Real, y::Real = x)
     sx, sy = coords(shape)
-    for i=linearindices(sx)
+    for i=1:length(sx)
         sx[i] += x
         sy[i] += y
     end
@@ -229,7 +229,7 @@ end
 function rotate!(shape::Shape, Θ::Real, c = center(shape))
     x, y = coords(shape)
     cx, cy = c
-    for i=linearindices(x)
+    for i=1:length(x)
         xi = rotate_x(x[i], y[i], Θ, cx, cy)
         yi = rotate_y(x[i], y[i], Θ, cx, cy)
         x[i], y[i] = xi, yi
@@ -506,7 +506,7 @@ function series_annotations_shapes!(series::Series, scaletype::Symbol = :pixels)
             push!(msize, maxscale)
             baseshape = _cycle(get(anns.baseshape),i)
             shape = scale(baseshape, msw*xscale/maxscale, msh*yscale/maxscale, (0,0))
-        end for i=linearindices(anns.strs)]
+        end for i=1:length(anns.strs)]
         series[:markershape] = shapes
         series[:markersize] = msize
     end

src/deprecated/backends/gadfly.jl

@@ -258,7 +258,7 @@ function addToGadflyLegend(plt::Plot, d::KW)
                 foundit = false
 
                 # extend the label if we found this color
-                for i in linearindices(guide.colors)
+                for i in 1:length(guide.colors)
                     if RGB(c) == guide.colors[i]
                         guide.labels[i] *= ", " * d[:label]
                         foundit = true
@@ -333,9 +333,9 @@ end
 #     # this is super weird, but... oh well... for some reason this creates n separate line segments...
 #     # create a list of vertices that go: [x1,x2,x2,x3,x3, ... ,xi,xi, ... xn,xn] (same for y)
 #     # then the vector passed to the "color" keyword should be a vector: [1,1,2,2,3,3,4,4, ..., i,i, ... , n,n]
-#     csindices = Int[mod1(i,length(cscheme.v)) for i in linearindices(d[:y])]
+#     csindices = Int[mod1(i,length(cscheme.v)) for i in 1:length(d[:y])]
 #     cs = collect(repmat(csindices', 2, 1))[1:end-1]
-#     grp = collect(repmat((linearindices(d[:y]))', 2, 1))[1:end-1]
+#     grp = collect(repmat((1:length(d[:y]))', 2, 1))[1:end-1]
 #     d[:x], d[:y] = map(createSegments, (d[:x], d[:y]))
 #     colorgroup = [(:linecolor, cs), (:group, grp)]
 

src/examples.jl

@@ -290,7 +290,7 @@ PlotExample("Layouts, margins, label rotation, title location",
     [:(begin
         plot(rand(100,6),layout=@layout([a b; c]),title=["A" "B" "C"],
                         title_location=:left, left_margin=[20mm 0mm],
-                        bottom_margin=10px, xrotation=60)
+                        bottom_margin=50px, xrotation=60)
     end)]
 ),
 
@@ -379,7 +379,7 @@ function test_examples(pkgname::Symbol; debug = false, disp = true, sleep = noth
                                         skip = [], only = nothing)
   Plots._debugMode.on = debug
   plts = Dict()
-  for i in linearindices(_examples)
+  for i in 1:length(_examples)
     only != nothing && !(i in only) && continue
     i in skip && continue
     try

src/recipes.jl

@@ -291,7 +291,7 @@ end
     hw = if bw == nothing
         0.5ignorenan_mean(diff(procx))
     else
-        Float64[0.5_cycle(bw,i) for i=linearindices(procx)]
+        Float64[0.5_cycle(bw,i) for i=1:length(procx)]
     end
 
     # make fillto a vector... default fills to 0
@@ -510,10 +510,8 @@ function _auto_binning_nbins{N}(vs::NTuple{N,AbstractVector}, dim::Integer; mode
     v = vs[dim]
 
     if mode == :auto
-        mode = :fd
-    end
-
-    if mode == :sqrt  # Square-root choice
+        30
+    elseif mode == :sqrt  # Square-root choice
         _cl(sqrt(n))
     elseif mode == :sturges  # Sturges' formula
         _cl(log2(n)) + 1
@@ -552,7 +550,7 @@ end
 
 
 @recipe function f(::Type{Val{:histogram}}, x, y, z)
-    seriestype := length(y) > 1e6 ? :stephist : :barhist
+    seriestype := :barhist
     ()
 end
 @deps histogram barhist
@@ -872,7 +870,7 @@ function get_xy(o::OHLC, x, xdiff)
 end
 
 # get the joined vector
-function get_xy(v::AVec{OHLC}, x = linearindices(v))
+function get_xy(v::AVec{OHLC}, x = 1:length(v))
     xdiff = 0.3ignorenan_mean(abs.(diff(x)))
     x_out, y_out = zeros(0), zeros(0)
     for (i,ohlc) in enumerate(v)

src/series.jl

@@ -69,13 +69,13 @@ end
 # TODO: can we avoid the copy here?  one error that crops up is that mapping functions over the same array
 #       result in that array being shared.  push!, etc will add too many items to that array
 
-compute_x(x::Void, y::Void, z)      = indices(z,1)
-compute_x(x::Void, y, z)            = indices(y,1)
+compute_x(x::Void, y::Void, z)      = 1:size(z,1)
+compute_x(x::Void, y, z)            = 1:size(y,1)
 compute_x(x::Function, y, z)        = map(x, y)
 compute_x(x, y, z)                  = copy(x)
 
 # compute_y(x::Void, y::Function, z)  = error()
-compute_y(x::Void, y::Void, z)      = indices(z,2)
+compute_y(x::Void, y::Void, z)      = 1:size(z,2)
 compute_y(x, y::Function, z)        = map(y, x)
 compute_y(x, y, z)                  = copy(y)
 
@@ -272,9 +272,9 @@ end
 # return a surface if this is a 3d plot, otherwise let it be sliced up
 @recipe function f{T<:Union{Integer,AbstractFloat}}(mat::AMat{T})
     if all3D(d)
-        inds = indices(mat)
+        n,m = size(mat)
         wrap_surfaces(d)
-        SliceIt, inds[2], inds[1], Surface(mat)
+        SliceIt, 1:m, 1:n, Surface(mat)
     else
         SliceIt, nothing, mat, nothing
     end

src/utils.jl

@@ -1,5 +1,5 @@
 
-calcMidpoints(edges::AbstractVector) = Float64[0.5 * (edges[i] + edges[i+1]) for i in linearindices(edges)-1]
+calcMidpoints(edges::AbstractVector) = Float64[0.5 * (edges[i] + edges[i+1]) for i in 1:length(edges)-1]
 
 "Make histogram-like bins of data"
 function binData(data, nbins)
@@ -43,7 +43,7 @@ function barHack(; kw...)
   # estimate the edges
   dists = diff(midpoints) * 0.5
   edges = zeros(length(midpoints)+1)
-  for i in linearindices(edges)
+  for i in 1:length(edges)
     if i == 1
       edge = midpoints[1] - dists[1]
     elseif i == length(edges)
@@ -56,7 +56,7 @@ function barHack(; kw...)
 
   x = Float64[]
   y = Float64[]
-  for i in linearindices(heights)
+  for i in 1:length(heights)
     e1, e2 = edges[i:i+1]
     append!(x, [e1, e1, e2, e2])
     append!(y, [fillrange, heights[i], heights[i], fillrange])

test/imgcomp.jl

@@ -92,7 +92,7 @@ function image_comparison_facts(pkg::Symbol;
                                 debug = false,  # print debug information?
                                 sigma = [1,1],  # number of pixels to "blur"
                                 eps = 1e-2)     # acceptable error (percent)
-  for i in linearindices(Plots._examples)
+  for i in 1:length(Plots._examples)
     i in skip && continue
     if only == nothing || i in only
       @test image_comparison_tests(pkg, i, debug=debug, sigma=sigma, eps=eps) |> success == true